CN117818371A - Active damping control method, device and computer readable storage medium - Google Patents

Abstract

The application discloses an active damping control method, an active damping control device and a computer readable storage medium, wherein the method comprises the following steps: and acquiring the motor rotating speed fluctuation quantity of the motor, inputting the motor rotating speed fluctuation quantity into an adaptive algorithm to calculate to obtain the torque compensation quantity of active damping, and finally compensating the motor torque through the torque compensation quantity. Therefore, the motor torque compensation quantity is calculated based on the self-adaptive algorithm, the motor torque is compensated through the torque compensation quantity, and when the speed abrupt change is counteracted, the vehicle body shakes caused by the backlash problem, the running safety of the vehicle is improved, and the driving and riding experience of a user is further improved.

Description

Active damping control method, device and computer readable storage medium

Technical Field

The present application relates to the technical field of new energy electric vehicles, and in particular to an active damping control method, device and computer-readable storage medium.

Background technique

With the shortage of non-renewable energy and the increasing environmental pollution, new energy vehicles are developing rapidly. During the driving process, if the gear backlash of the vehicle is large and the vehicle speed changes suddenly, the vehicle body will shake, thus reducing the user's driving and riding experience.

It can be seen that how to solve the problem of gear clashing in new energy vehicles, avoid body shaking caused by sudden speed changes and large gear tooth gaps, improve the vehicle's anti-interference ability, and thereby improve the user's driving and riding experience, is an issue that needs to be urgently resolved by technical personnel in this field.

Summary of the invention

In view of this, one aspect of the present application provides an active damping control method, the method comprising:

Get the motor speed fluctuation of the motor;

Inputting the motor speed fluctuation into an adaptive algorithm to calculate the torque compensation of active damping;

The motor torque is compensated by the torque compensation amount.

Another aspect of the present application provides an active damping control device, the device comprising:

An acquisition module, used for acquiring the motor speed fluctuation of the motor;

A calculation module, used for inputting the motor speed fluctuation into an adaptive algorithm to calculate and obtain a torque compensation amount of active damping;

The compensation module is used to compensate the motor torque by using the torque compensation amount.

Another aspect of the present application provides an active damping control device, the device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the active damping control method are implemented.

Another aspect of the present application provides a computer-readable storage medium, and when the program is executed by a processor, the steps of the active damping control method are implemented.

An active damping control method, device and computer-readable storage medium provided in the present application have the following beneficial effects: the motor torque compensation amount is calculated based on an adaptive algorithm, and the motor torque is compensated by the torque compensation amount, so as to offset the body vibration caused by the tooth clearance problem when the speed changes suddenly, improve the vehicle driving safety, and further improve the user's driving and riding experience.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a schematic flow chart of an active damping control method provided in an embodiment of the present application;

FIG2 is a control block diagram of an active damping control method provided in an embodiment of the present application;

FIG3 is a flow chart of an active damping control method provided by another embodiment of the present application;

FIG4 is a schematic diagram of the result of an active damping control method provided in an embodiment of the present application;

FIG5 is a schematic structural diagram of an active damping control device provided by another embodiment of the present application;

FIG6 is a schematic structural diagram of an active damping control device provided in yet another embodiment of the present application.

The reference numerals are as follows: 60 is a memory, 61 is a processor, 62 is a display screen, 63 is an input/output interface, 64 is a communication interface, 65 is a power supply, 66 is a communication bus, 601 is a computer program, 602 is an operating system, and 603 is data.

Detailed ways

Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and/or" used in this article refers to and includes any or all possible combinations of one or more associated listed items.

It should be understood that although the terms first, second, third, etc. may be used in the present application to describe various information, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

With the rapid development of new energy vehicles, the problem of automobile gear clubbing has always been a crucial research direction. Automobile gear clubbing refers to the situation where when a car's speed suddenly changes during driving, the gear tooth gap causes the car to not mesh smoothly or a hard collision occurs, which in turn causes the car body to shake, affecting the vehicle's gear shifting and safe driving, and reducing the user's driving and riding experience.

In order to solve the above technical problems, an embodiment of the present application provides an active damping control method, which calculates the torque compensation amount through an adaptive algorithm, and thereby compensates the motor torque through the torque compensation amount, thereby offsetting the body vibration caused by the tooth gap when the vehicle has a sudden speed change, thereby improving the vehicle driving safety.

FIG1 is a flow chart of an active damping control method provided in an embodiment of the present application. As shown in FIG1 , the method includes:

S10: Obtain the motor speed fluctuation of the motor.

Figure 2 is a control block diagram of an active damping control method provided in an embodiment of the present application. In a specific embodiment, when the compensation for the motor is achieved by calculating the torque compensation amount, as shown in Figure 2, the speed fluctuation of the motor is first obtained. It should be noted that the speed fluctuation of the motor refers to the error between the actual speed of the motor and the speed after filtering the actual speed (target speed).

In the implementation, the motor speed fluctuation amount is determined. In addition to calculating the torque compensation amount, as shown in FIG2 , after the motor speed fluctuation amount is obtained, the rated torque amount can also be generated through PI control.

It should be noted that, in some optional embodiments, the actual rotation speed of the motor can be collected and acquired by corresponding sensors, and this application does not specifically limit the method for acquiring the motor rotation speed.

S11: Input the motor speed fluctuation into the adaptive algorithm to calculate and obtain the torque compensation of active damping.

S12: Compensate the motor torque through the torque compensation amount.

After the motor speed fluctuation is obtained in step S10, the motor speed fluctuation is transmitted to the adaptive algorithm for calculation to obtain the torque compensation of active damping. It can be understood that the torque compensation refers to the torque loss caused by external factors under certain specific working conditions, which is an additional torque value added to the motor torque. After increasing the torque value to compensate for the torque loss, the vehicle body vibration caused by the sudden change in speed and the backlash can be offset.

It is understandable that when calculating the torque compensation, since adaptive control can maintain good performance when the system characteristics change, it has a certain resistance to model inaccuracy, noise and external interference, and can improve the robustness of the motor system. In addition, the controller parameters can be quickly adjusted according to the real-time feedback information of the motor to ensure the accuracy of the calculation of the torque compensation. Therefore, calculating the torque compensation by an adaptive algorithm can effectively solve the problem of vehicle gear slapping.

It is worth noting that, in some optional embodiments, the adaptive algorithm may be model reference adaptation or feedforward adaptive control, which is not specifically limited in the present application.

Furthermore, the motor torque is compensated by the torque compensation amount to compensate for the loss of the motor torque. Specifically, as shown in FIG2 , the torque compensation amount calculated by the adaptive algorithm, the rated torque amount calculated by the PI algorithm, and the feedback torque calculated according to the motor DQ axis current are combined to calculate the target torque T finally input to the inverter.

Therefore, the active damping control method provided in the embodiment of the present application includes: obtaining the motor speed fluctuation of the motor, and inputting the motor speed fluctuation into the adaptive algorithm to calculate the torque compensation of the active damping, and finally, compensating the motor torque by the torque compensation. Therefore, the motor torque compensation is calculated based on the adaptive algorithm, and the motor torque is compensated by the torque compensation, so as to offset the body vibration caused by the backlash problem when the speed changes suddenly, improve the driving safety of the vehicle, and then improve the driving and riding experience of the user.

In order to improve the efficiency and accuracy of torque compensation, as a preferred embodiment, the adaptive algorithm can be a model reference adaptive control algorithm. It can be understood that the model reference adaptive control algorithm has the advantages of simple design, easy implementation, high tolerance to uncertainty, and the ability to achieve rapid response. Therefore, in a preferred embodiment, the adaptive algorithm can be a model reference adaptive control algorithm.

Therefore, the active damping control method provided in the embodiment of the present application optimizes the adaptive algorithm to be a model reference adaptive control algorithm, which can achieve fast and accurate compensation of the motor torque and improve the safety and reliability of the motor system.

FIG3 is a flow chart of an active damping control method provided by another embodiment of the present application. Based on the above embodiment, as an optional embodiment, as shown in FIG3 , the motor speed fluctuation is input into the adaptive algorithm to calculate the torque compensation amount of the active damping, which includes:

S30: Obtaining the mechanical motion equation of the motor;

In a specific embodiment, the mechanical motion equation of the motor can be expressed as:

Among them, _Te is the electromagnetic torque of the motor, _TL is the load torque of the motor, J is the torque inertia, B is the damping coefficient, and _ωm is the actual motor speed of the motor.

S31: Determine the first-order differential equation of the reference model in the model reference adaptive control algorithm according to the mechanical motion equation.

In order to achieve fast speed tracking performance, the reference model output _ωd of the reference model in the model reference adaptive control algorithm is compared with the target speed error, where the target speed error is the error between the actual speed _ωm and the desired speed. Under the action of the adaptive mechanism, the speed error can quickly track the output of the reference model and converge to 0. Therefore, according to the mechanical motion equation of the motor, formula (1) can determine the first-order differential equation form of the reference model in the model reference adaptive control algorithm:

Among them, _ωd is the output of the reference model and _τd is a positive constant.

It should be noted that since the mechanical motion equation of the motor in formula (1) is in the form of a first-order differential equation, when selecting the reference model in the model reference adaptive control algorithm, the mechanical motion equation based on the motor is selected as the first-order differential equation shown in formula (2).

S32: Convert the first-order differential equation into an exponential decay form to obtain the target equation.

Furthermore, by converting formula (2) into an exponential decay form, the target equation is obtained as follows:

Where c is a positive constant determined by the initial state.

S33: Determine the error dynamic equation in the model reference adaptive control algorithm according to the mechanical motion equation, the target equation and the motor speed fluctuation.

The error dynamic equation in the reference adaptive algorithm is determined according to the mechanical motion equation (formula (1)), the target equation (formula (3)) and the motor speed fluctuation. Specifically, the electromagnetic torque _Te , the load torque T _L , the torque inertia J and the damping coefficient B can be determined according to formula (1). The reference model output _ωd can be determined according to formula (3). In addition, the motor speed fluctuation is the difference between the actual motor speed _ωm and the speed (target speed) _ωr after filtering the actual speed.

From this, the error dynamic equation in the model reference adaptive control algorithm can be obtained:

Among them, ω _m is the actual speed of the motor, and ω _r is the target speed after filtering the actual speed ω _m .

S34: Define the combined tracking error based on the error dynamics equation.

Further, the combined tracking error can be defined according to the error dynamic equation determined in step S33:

σ＝δe ₁ +e ₂ (5)

Among them, σ is the combined group error, δ is a coefficient, and _e1 and _e2 are two vectors obtained by transformation according to formula (4).

It should be noted that the combined tracking error refers to the difference between the actual system output and the ideal reference model output. This difference is used to drive the controller parameter adjustment process to make the dynamic characteristics of the actual system as close as possible to the selected reference model.

S35: Determine the torque compensation amount according to the combined tracking error.

Determine the torque compensation amount based on the obtained combined follower error σ. Specifically, As the torque compensation (or adaptive compensation term), where: is the estimated value of the actual torque value Γ ^* , that is, is the estimated torque value, the estimated torque value The update method is:

in, is a positive adaptive scaling factor, /> and/> are a vector, torque estimate/> is bounded.

Furthermore, the torque estimate It can be written as:

According to formula (7), the torque compensation amount (adaptive compensation term) can be obtained:

In a specific embodiment, as shown in FIG2 , the speed fluctuation is input into the model reference adaptive control algorithm to calculate the torque compensation The rated torque T ₁ is generated through PI control, and the feedback torque T ₂ is calculated based on the motor DQ axis current.

Specifically, the rated torque T ₁ is obtained according to formula (5), that is, T ₁ =-kσ.

Therefore, the torque calculation module shown in FIG2 can calculate the final target torque T of the input inverter as:

Figure 4 is a schematic diagram of the results of an active damping control method provided in an embodiment of the present application. In a specific embodiment, simulink is used for simulation, and the speed fluctuation of the motor before and after the active damping is added is tested at 600 rpm. As shown in Figure 4, after adding the active damping control method provided in an embodiment of the present application, the speed fluctuation is reduced from 587r/min to 598r/min, thereby avoiding the problem of vehicle gear knocking.

It can be seen that the active damping control method provided in the embodiment of the present application is based on a dual closed loop of speed and torque. It calculates the torque compensation amount of the motor through a model reference adaptive control algorithm, and compensates for the motor torque loss through the torque compensation amount. It can achieve fast and accurate compensation, avoid the problem of gear knocking when the speed of the vehicle changes suddenly, and improve the driving safety of the vehicle.

In an optional embodiment, obtaining the motor speed fluctuation of the motor includes:

Get the actual motor speed of the motor;

Filter the actual motor speed to obtain the target speed;

The difference between the target speed and the actual speed of the motor is taken as the motor speed fluctuation.

In a specific embodiment, the actual motor speed ω _m of the motor is obtained, and the actual motor speed ω _m is filtered to obtain the filtered target speed ω _r . Among them, when filtering, a first-order low-pass filter can be selected, a second-order low-pass filter can be selected, and a Kalman filter can also be selected, which is not specifically limited in this application. However, the speed after Kalman filtering is the smoothest, but the response efficiency is low, and the first-order low-pass filter has the fastest response efficiency, but the filtering effect is poor. Therefore, in order to take into account the filtering effect and the response rate, the embodiment of the present application preferably uses a second-order low-pass filter to filter the actual motor speed ω _m .

The actual motor speed ω _m and the target speed ω _r are obtained, and the difference between the two is taken as the motor speed fluctuation.

Therefore, the active damping control method provided in the embodiment of the present application filters the actual motor speed through a second-order low-pass filter, which ensures the filtering efficiency while making the filtered target speed smoother, thereby improving the accuracy of torque compensation.

In a specific embodiment, compensating the motor torque by the torque compensation amount includes:

Get the DQ axis current of the motor;

Calculate feedback torque based on DQ axis current;

Calculate the target torque according to the feedback torque and the torque compensation amount;

Input the target torque to the motor.

In a specific implementation, the DQ axis current of the motor at the current moment (i.e., the direct axis current and quadrature axis current of the motor) is obtained. It should be noted that the acquisition can be performed by a current sensor, which is not limited in this application. Further, the feedback torque T ₂ is calculated according to the DQ axis current at the current moment, so as to obtain the feedback torque T ₂ and the torque compensation amount. Calculate the target torque T.

As shown in FIG2 , in a specific embodiment, after filtering the actual motor speed ω _m , a delay problem will be generated due to filtering, thereby reducing the efficiency of motor speed compensation. In order to avoid this technical problem, in a preferred embodiment, delay compensation is used to avoid the delay problem caused by filtering. Specifically, obtaining the DQ axis current of the motor includes:

Get the DQ axis current of the motor at the current moment;

The DQ axis current at the next moment is predicted according to the DQ axis current at the current moment to obtain the DQ axis predicted current, which is used to compensate for the delay caused when filtering the actual speed of the motor. The DQ axis current is the DQ axis predicted current.

Among them, the DQ axis current expression at the current moment can be expressed as:

Wherein, i _d is the direct-axis (d-axis) current, i _q is the quadrature-axis (q-axis) current, L _d is the direct-axis (d-axis) inductance of the motor stator winding, L _q is the direct-axis (q-axis) inductance of the motor stator winding, R _s is the resistance of the motor stator winding, ω _n is the mechanical angular velocity of the motor, ω _e is the electrical angular velocity of the motor, and ψ _f is the magnetic flux generated by the permanent magnet.

According to formula (10), the DQ axis current at the next moment is predicted to obtain the predicted current:

Wherein, _Ts is the sampling period, k represents the current moment, and k+1 represents the next moment. That is, the DQ axis current at the current moment is calculated according to formula (10), and the predicted current is predicted according to formula (11).

Furthermore, the feedback torque T ₂ is obtained, that is, Among them, p is the number of pole pairs, _ψd is the direct-axis flux, and _ψq is the quadrature-axis flux.

Therefore, the active damping control method provided in the embodiment of the present application avoids the delay caused by filtering the actual speed of the motor through delay compensation, improves the efficiency of motor torque compensation, and further improves the reliability of the vehicle motor system.

In the above embodiments, the active damping control method is described in detail, and the present application also provides an embodiment corresponding to an active damping control device. It should be noted that the present application describes the embodiments of the device part from two perspectives, one is based on the perspective of functional modules, and the other is based on the perspective of hardware structure.

FIG5 is a schematic diagram of the structure of an active damping control device provided by another embodiment of the present application. As shown in FIG5 , the device includes:

An acquisition module 50 is used to acquire the motor speed fluctuation of the motor;

A calculation module 51 is used to input the motor speed fluctuation into an adaptive algorithm to calculate the torque compensation of active damping;

The compensation module 52 is used to compensate the motor torque by using the torque compensation amount.

In addition, the active damping control device provided in the embodiment of the present application further includes:

A motor mechanical motion equation acquisition module, used to acquire the mechanical motion equation of the motor;

A determination module, used to determine the first-order differential equation of the reference model in the model reference adaptive control algorithm according to the mechanical motion equation;

A conversion module, used for converting the first-order differential equation into an exponential decay form to obtain a target equation;

An error dynamic equation determination module, used to determine the error dynamic equation in the model reference adaptive control algorithm according to the mechanical motion equation, the target equation and the motor speed fluctuation amount;

A definition module, used for defining a combined tracking error based on the error dynamic equation;

The torque compensation amount determination module is used to determine the torque compensation amount according to the combined tracking error.

A motor actual speed acquisition module, used to acquire the motor actual speed of the motor;

A filtering module, used for filtering the actual speed of the motor to obtain a target speed;

A processing module is used to use the difference between the target speed and the actual speed of the motor as the motor speed fluctuation amount.

A DQ axis current acquisition module, used to acquire the DQ axis current of the motor;

A feedback torque calculation module, used for calculating the feedback torque according to the DQ axis current;

a target torque calculation module, used for calculating the target torque according to the feedback torque and the torque compensation amount;

An input module is used to input the target torque into the motor.

For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can refer to the partial description of the method embodiments. The device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present application. A person of ordinary skill in the art can understand and implement it without creative work.

FIG6 is a schematic diagram of the structure of an active damping control device provided by another embodiment of the present application. As shown in FIG6 , the active damping control device includes: a memory 60 for storing a computer program;

The processor 61 is used to implement the steps of the active damping control method mentioned in the above embodiment when executing the computer program.

The active damping control device provided in this embodiment may include but is not limited to a vehicle controller or other vehicle controllers.

Among them, the processor 61 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 61 can be implemented in at least one hardware form of a digital signal processor (Digital Signal Processor, referred to as DSP), a field programmable gate array (Field-Programmable Gate Array, referred to as FPGA), and a programmable logic array (Programmable Logic Array, referred to as PLA). The processor 61 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a central processing unit (Central Processing Unit, referred to as CPU); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 61 may be integrated with a graphics processing unit (Graphics Processing Unit, referred to as GPU), and the GPU is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 61 may also include an artificial intelligence (Artificial Intelligence, referred to as AI) processor, which is used to process computing operations related to machine learning.

The memory 60 may include one or more computer-readable storage media, which may be non-transitory. The memory 60 may also include a high-speed random access memory, and a non-volatile memory, such as one or more disk storage devices, flash memory storage devices. In this embodiment, the memory 60 is at least used to store the following computer program 601, wherein, after the computer program is loaded and executed by the processor 61, it can implement the relevant steps of the active damping control method disclosed in any of the aforementioned embodiments. In addition, the resources stored in the memory 60 may also include an operating system 602 and data 603, etc., and the storage method may be temporary storage or permanent storage. Among them, the operating system 602 may include Windows, Unix, Linux, etc. Data 603 may include but is not limited to relevant data designed in the active damping control method, etc.

In some embodiments, the active damping control device may further include a display screen 62 , an input/output interface 63 , a communication interface 64 , a power supply 65 , and a communication bus 66 .

Those skilled in the art will appreciate that the structure shown in FIG. 6 does not constitute a limitation on the active damping control device, and may include more or fewer components than those shown in the figure.

The active damping control device provided in the embodiment of the present application includes a memory and a processor. When the processor executes the program stored in the memory, it can implement the active damping control method in the above embodiment.

Finally, the present application also provides an embodiment corresponding to a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps recorded in the above method embodiment are implemented.

Although this specification includes many specific implementation details, these should not be interpreted as limiting the scope of any invention or the scope of protection claimed, but are mainly used to describe the features of the specific embodiments of a particular invention. Certain features described in multiple embodiments in this specification may also be implemented in combination in a single embodiment. On the other hand, the various features described in a single embodiment may also be implemented separately in multiple embodiments or in any suitable sub-combination. In addition, although features may work in certain combinations as described above and even initially claimed as such, one or more features from the claimed combination may be removed from the combination in some cases, and the claimed combination may point to a sub-combination or a variation of a sub-combination.

Similarly, although operations are depicted in a particular order in the accompanying drawings, this should not be understood as requiring that these operations be performed in the particular order shown or performed sequentially, or requiring that all illustrated operations be performed to achieve the desired results. In some cases, multitasking and parallel processing may be advantageous. In addition, the separation of various system modules and components in the above-described embodiments should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product, or packaged into multiple software products.

Thus, specific embodiments of the subject matter have been described. Other embodiments are within the scope of the appended claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the particular order or sequential order shown to achieve the desired results. In some implementations, multitasking and parallel processing may be advantageous.

The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims (10)

1. An active damping control method, characterized in that the method comprises: Get the motor speed fluctuation of the motor; Inputting the motor speed fluctuation into an adaptive algorithm to calculate the torque compensation of active damping; The motor torque is compensated by the torque compensation amount. 2. The active damping control method according to claim 1, characterized in that the adaptive algorithm is a model reference adaptive control algorithm. 3. The active damping control method according to claim 2, characterized in that the step of inputting the motor speed fluctuation into an adaptive algorithm to calculate the torque compensation amount of active damping comprises: Obtaining a mechanical motion equation of the motor; Determining a first-order differential equation of a reference model in the model reference adaptive control algorithm according to the mechanical motion equation; Converting the first-order differential equation into an exponential decay form to obtain a target equation; Determine the error dynamic equation in the model reference adaptive control algorithm according to the mechanical motion equation, the target equation and the motor speed fluctuation; defining a combined tracking error based on the error dynamics equation; The torque compensation amount is determined according to the combined tracking error. 4. The active damping control method according to claim 1, wherein obtaining the motor speed fluctuation of the motor comprises: Obtaining the actual motor speed of the motor; Filtering the actual speed of the motor to obtain a target speed; The difference between the target speed and the actual speed of the motor is used as the motor speed fluctuation amount. 5. The active damping control method according to claim 4, wherein filtering the actual speed of the motor to obtain the target speed comprises: The target speed is obtained by filtering the actual speed of the motor through a second-order low-pass filter. 6. The active damping control method according to claim 4, wherein compensating the motor torque by the torque compensation amount comprises: Obtaining the DQ axis current of the motor; Calculating the feedback torque according to the DQ axis current; Calculating a target torque according to the feedback torque and the torque compensation amount; The target torque is input to the motor. 7. The active damping control method according to claim 6, wherein obtaining the DQ axis current of the motor comprises: Obtaining the DQ axis current of the motor at the current moment; The DQ axis current at the next moment is predicted based on the DQ axis current at the current moment to obtain the DQ axis predicted current, which is used to compensate for the delay generated when filtering the actual speed of the motor. The DQ axis current is the DQ axis predicted current. 8. An active damping control device, characterized in that the device comprises: An acquisition module, used for acquiring the motor speed fluctuation of the motor; A calculation module, used for inputting the motor speed fluctuation into an adaptive algorithm to calculate and obtain a torque compensation amount of active damping; The compensation module is used to compensate the motor torque by using the torque compensation amount. 9. An active damping control device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the active damping control method as claimed in any one of claims 1 to 7 when executing the program. 10. A computer-readable storage medium having a computer program stored thereon, wherein when the program is executed by a processor, the steps of the active damping control method according to any one of claims 1 to 7 are implemented.